Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test.

ABSTRACT: The spatial organization of the genome plays a critical role in regulating gene expression. Recent chromatin interaction mapping studies have revealed that topologically associating domains and subdomains are fundamental building blocks of the three-dimensional genome. Identifying such hierarchical structures is a critical step toward understanding the three-dimensional structure-function relationship of the genome. Existing computational algorithms lack statistical assessment of domain predictions and are computationally inefficient for high-resolution Hi-C data. We introduce the Gaussian Mixture model And Proportion test (GMAP) algorithm to address the above-mentioned challenges. Using simulated and experimental Hi-C data, we show that domains identified by GMAP are more consistent with

SUBMITTER: Yu W 

PROVIDER: S-EPMC5599511 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature